#RStudio Version 1.2.1335
sessionInfo()
#R version 3.5.3 (2019-03-11)
#Platform: x86_64-w64-mingw32/x64 (64-bit)
#Running under: Windows >= 8 x64 (build 9200)
Hello I have created a function called autocorrelate.
When I run it with ggplot I get this error:
#Error in autocorrelate(., NetEditRev, lags = 0:nrow(.)) : unused argument
(lags = 0:nrow(.))
Using what I learned from Rui yesterday I have tried to track down the problem
myself
#---------------------------------- ggplot ISSUE 2
-----------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
getAnywhere('lags')
# A single object matching 'lags' was found
# It was found in the following places
# package:TTR
# namespace:TTR
# with value
function (x, n = 1)
{
x <- as.matrix(x)
if (is.null(colnames(x)))
colnames(x) <- paste("V", 1:NCOL(x), sep = "")
out <- embed(x, n + 1)
if (n == 1)
lag.names <- 1
else if (NCOL(x) == 1)
lag.names <- 1:n
else lag.names <- rep(1:n, NCOL(x))
colnames(out) <- c(colnames(x), paste(colnames(x), sort(lag.names),
sep = "."))
return(out)
}
<bytecode: 0x0000021163065658>
# <environment: namespace:TTR>
#Here are references I have perused but not sure they help, or at least I do
not understand how they help me?
https://stackoverflow.com/questions/32056718/annotate-ggplot-bar-chart-error-unused-arguments
#https://stackoverflow.com/questions/24004974/sudden-unused-argument-error
find("lags")
#"package:TTR"
#Here are the Pkgs/libraries loaded, and I see TTR_0.23-4
# I did not load this library so it must be coming in with another library?
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] plotly_4.9.0 tseries_0.10-46 timeDate_3043.102
h2o_3.22.1.1 lime_0.4.1
[6] parsnip_0.0.2 sweep_0.2.1.1 forecast_8.7
riem_0.1.1 timetk_0.1.1.1
[11] tidyquant_0.5.6 forcats_0.4.0 stringr_1.4.0
dplyr_0.8.1 purrr_0.3.2
[16] readr_1.3.1 tidyr_0.8.3 tibble_2.1.1
ggplot2_3.1.1 tidyverse_1.2.1
[21] quantmod_0.4-14 TTR_0.23-4
PerformanceAnalytics_1.5.2 xts_0.11-2 zoo_1.8-5
[26] lubridate_1.7.4 yardstick_0.0.3
?`TTR-package`
These are the libraries I have loaded
library(yardstick)
library(tidyquant)
library(timetk)
library(riem)
library(forecast)
library(sweep)
library(parsnip)
library(lime)
library(h2o)
library(timeDate)
library(tseries)
library(ggplot2)
library(tidyverse)
library(lubridate)
library(plotly)
I tried changing lags to lags1 in the function but that did not help
Here are the script and a data sample to assist anyone who might try to help me.
Thank you for any advice.
WHP
#Create a function----
autocorrelate <- function(dftmp, value, Lags = 0.20) {
value_expr <- enquo(value)
acf_values <- dftmp %>%
select(!! value_expr) %>%
pull() %>%
acf(lag.max = tail(lags, 1), plot = FALSE) %>%
.$acf %>%
.[,,1]
ret <- tibble(acf = acf_values) %>%
rowid_to_column(var = "lag") %>%
mutate(lag = lag - 1) %>%
filter(lag %in% lags)
return(ret)
}
g2 <- as_tibble(dftmp) %>%
autocorrelate(NetEditRev,lags = 0:nrow(.)) %>%
ggplot(aes(lag,acf)) +
geom_point(alpha = 0.5, color = "#2c3e50") +
expand_limits(y = c(-1,1)) +
theme_tq() +
labs(title = "Autocorrelation For Net Edit Revenue")
#And I get --> Error in autocorrelate(., NetEditRev, lags = 0:nrow(.)) :
unused argument (lags = 0:nrow(.))
#Notice in the error it looks like autocorrelate(., yet there is no ., in my
script?
ggplotly(g2)
str(dftmp)
'data.frame':892 obs. of 10 variables:
$ Date2 : Date, format: "2017-01-01" "2017-01-02" "2017-01-03"
"2017-01-04" ...
$ NetEditRev: num -923 19222 -8397 37697 46075 ...
$ index.num : int 1483228800 1483315200 1483401600 1483488000 1483574400
1483660800 1483747200 1483833600 1483920000 1484006400 ...
$ year : int 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 ...
$ half : int 1 1 1 1 1 1 1 1 1 1 ...
$ quarter : int 1 1 1 1 1 1 1 1 1 1 ...
$ month.lbl : Ord.factor w/ 12 levels "January"<"February"<..: 1 1 1 1 1 1 1 1
1 1 ...
$ day : int 1 2 3 4 5 6 7 8 9 10 ...
$ wday.lbl : Ord.factor w/ 7 levels "Sunday"<"Monday"<..: 1 2 3 4 5 6 7 1 2 3
...
$ holiday : num 0 1 0 0 0 0 0 0 0 0 ...
Here is a sample of my df
head(dftmp,n=35)
Date2 NetEditRev index.num year half quarter month.lbl day wday.lbl
holiday
1 2017-01-01 -923.40 1483228800 2017 1 1 January 1 Sunday
0
2 2017-01-02 19222.09 1483315200 2017 1 1 January 2 Monday
1
3 2017-01-03 -8396.82 1483401600 2017 1 1 January 3 Tuesday
0
4 2017-01-04 37696.58 1483488000 2017 1 1 January 4 Wednesday
0
5 2017-01-05 46075.34 1483574400 2017 1 1 January 5 Thursday
0
6 2017-01-06 38329.35 1483660800 2017 1 1 January 6 Friday
0
7 2017-01-07 3110.51 1483747200 2017 1 1 January 7 Saturday
0
8 2017-01-08 21.39 1483833600 2017 1 1 January 8 Sunday
0
9 2017-01-09 63569.67 1483920000 2017 1 1 January 9 Monday
0
10 2017-01-10 50777.00 1484006400 2017 1 1 January 10 Tuesday
0
11 2017-01-11 55548.60 1484092800 2017 1 1 January 11 Wednesday
0
12 2017-01-12 70217.73 1484179200 2017 1 1 January 12 Thursday
0
13 2017-01-13 62536.15 1484265600 2017 1 1 January 13 Friday
0
14 2017-01-14 2696.83 1484352000 2017 1 1 January 14 Saturday
0
15 2017-01-15 2230.00 1484438400 2017 1 1 January 15 Sunday
0
16 2017-01-16 56310.90 1484524800 2017 1 1 January 16 Monday
1
17 2017-01-17 58521.93 1484611200 2017 1 1 January 17 Tuesday
0
18 2017-01-18 50057.73 1484697600 2017 1 1 January 18 Wednesday
0
19 2017-01-19 57366.70 1484784000 2017 1 1 January 19 Thursday
0
20 2017-01-20 61390.94 1484870400 2017 1 1 January 20 Friday
0
21 2017-01-21 1839.09 1484956800 2017 1 1 January 21 Saturday
0
22 2017-01-22 807.57 1485043200 2017 1 1 January 22 Sunday
0
23 2017-01-23 72209.44 1485129600 2017 1 1 January 23 Monday
0
24 2017-01-24 70799.21 1485216000 2017 1 1 January 24 Tuesday
0
25 2017-01-25 70240.88 1485302400 2017 1 1 January 25 Wednesday
0
26 2017-01-26 51462.66 1485388800 2017 1 1 January 26 Thursday
0
27 2017-01-27 46852.37 1485475200 2017 1 1 January 27 Friday
0
28 2017-01-28 2396.67 1485561600 2017 1 1 January 28 Saturday
0
29 2017-01-29 2051.62 1485648000 2017 1 1 January 29 Sunday
0
30 2017-01-30 72561.32 1485734400 2017 1 1 January 30 Monday
0
31 2017-01-31 69630.69 1485820800 2017 1 1 January 31 Tuesday
0
32 2017-02-01 -17304.22 1485907200 2017 1 1 February 1 Wednesday
0
33 2017-02-02 11773.84 1485993600 2017 1 1 February 2 Thursday
0
34 2017-02-03 20703.69 1486080000 2017 1 1 February 3 Friday
0
35 2017-02-04 2762.87 1486166400 2017 1 1 February 4 Saturday
0
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